Junior AI Engineer, Legal Tech — Shape Contract AI

SpotDraft; United States; On-site; USD 90,000 - 125,000; Full time

Job summary

SpotDraft is seeking a Junior Applied AI Engineer to help build production AI systems powering our legal‑tech products. You will work with senior engineers to develop distributed AI services that process large volumes of documents, optimize LLM performance, and ensure reliability in a SaaS environment.

Ideal candidates have hands-on experience with LLMs, prompt engineering, and Python, and enjoy collaborating across teams to improve features, reduce costs, and push the boundaries of legal tech.

Qualifications

• Upto 3 years of software/ML engineering experience with exposure to LLM-based systems.
• Experience integrating LLM APIs (GPT-4, Claude, Gemini, or Llama) and prompt engineering.
• Know-how of context engineering — structuring, trimming, and managing what gets passed into the model's context window across a workflow.
• Understanding of agent loops and graphs — how agentic control flow works (e.g. ReAct-style loops, state graphs, conditional branching between steps/tools).
• Hands-on experience building agentic workflows — chaining tool calls, managing state across turns, and handling multi-step reasoning.
• Experience building or contributing to eval systems — writing test cases, scoring outputs, and tracking quality/regression over time.
• Solid Python skills with an understanding of core software engineering practices (testing, version control, code review).
• Foundational understanding of transformer architectures, embeddings, and how LLMs work.
• Some exposure to vector databases and semantic search concepts
• Familiarity with async programming and API frameworks (FastAPI or similar)
• Basic understanding of data structures, algorithms, and complexity
• Comfort working in a fast-paced environment and learning quickly from senior engineers and code reviews.

Responsibilities

• Build AI features using transformer-based architectures for legal document workflows.
• Contribute to agentic systems with ReAct-style flows and tool calling.
• Write and refine prompts and manage prompt libraries and versioning.
• Build retrieval pipelines: chunking, BM25, and dense embeddings.
• Assist in retrieval-grounded generation and context window tuning.
• Work with vector databases to support semantic search features.
• Develop API services that call LLM providers with retry logic, rate limiting, and fallbacks.
• Support inference optimization: caching, batching, and latency/cost monitoring.
• Write production-grade Python code within existing service architectures.
• Develop evaluation scripts and datasets to measure model quality and regression.
• Participate in A/B testing of prompts, models, and configurations.
• ML Ops: CI/CD pipelines, containerization, basic Kubernetes; monitoring dashboards; debugging with logs.

Skills

LLM API integration

Context engineering

Agent loops

Agentic workflows

Eval systems

Python programming

Transformer architectures

Vector databases

Async programming

Data structures & algorithms

Tools

Docker

FastAPI

Kubernetes

AWS

GCP

Azure

LangChain

Weaviate

Job description

SpotDraft is seeking a Junior Applied AI Engineer to help build production AI systems powering our legal‑tech products. You will work with senior engineers to develop distributed AI services that process large volumes of documents, optimize LLM performance, and ensure reliability in a SaaS environment.

Ideal candidates have hands-on experience with LLMs, prompt engineering, and Python, and enjoy collaborating across teams to improve features, reduce costs, and push the boundaries of legal tech.